Metadata-Version: 2.4
Name: surfinBH
Version: 1.2.7
Summary: Surrogate Final BH properties.
Home-page: https://github.com/vijayvarma392/surfinBH
Author: Vijay Varma
Author-email: vvarma@caltech.edu
Keywords: black-holes gravitational-waves Gaussian-process-regression
Classifier: Intended Audience :: Science/Research
Classifier: Natural Language :: English
Classifier: Topic :: Scientific/Engineering :: Physics
Classifier: Topic :: Scientific/Engineering :: Astronomy
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy
Requires-Dist: scipy
Requires-Dist: h5py
Requires-Dist: scikit-learn>=0.19.1
Requires-Dist: lalsuite>=6.70
Requires-Dist: gwsurrogate
Dynamic: author
Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
Dynamic: keywords
Dynamic: license-file
Dynamic: requires-dist
Dynamic: summary

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# Welcome to surfinBH!

<img src="https://raw.githubusercontent.com/vijayvarma392/surfinBH/master/images/interaction.jpeg" alt="BHScattering" width="600px"/>

<br/>

_**surfinBH**_ provides _**sur**rogate **fin**al **B**lack_ _**H**ole_
properties for mergers of binary black holes (BBH).

These fits are described in the following papers: <br/>
[1] V. Varma, D. Gerosa, L. C. Stein, F. Hébert and H. Zhang,
[arxiv:1809.09125](https://arxiv.org/abs/1809.09125).

[2] V. Varma, S. E. Field, M. A. Scheel, J. Blackman, D. Gerosa, L. C.
Stein, L. E. Kidder, H. P. Pfeiffer,
[arxiv:1905.09300](https://arxiv.org/abs/1905.09300).

[3] M. Boschini, D. Gerosa, V. Varma, et al.,
[arXiv:2307.03435](https://arxiv.org/abs/2307.03435)

[4] L. Magaña Zertuche, L. C. Stein, et al.,
[arXiv:2408.05300](https://arxiv.org/abs/2408.05300)

[5] G. Da Re, K. Mitman, L. C. Stein, et al.,
[arXiv:2503.09569](https://arxiv.org/abs/2503.09569)

If you find this package useful in your work, please cite reference [1] and,
if available, the relevant paper describing the particular model. Please also
cite this package, see the DOI badge at the top of this page for BibTeX keys.

This package lives on [GitHub](https://github.com/vijayvarma392/surfinBH), is
compatible with `python3`, and is tested every week. You can see the current
build status of the master branch at the top of this page.

## Installation

### PyPI
_**surfinBH**_ is available through [PyPI](https://pypi.org/project/surfinBH/):

```shell
pip install surfinBH
```

### Conda
_**surfinBH**_ is available on [conda-forge](https://anaconda.org/conda-forge/surfinbh):

```shell
conda install -c conda-forge surfinbh
```


### From source

```shell
git clone git@github.com:vijayvarma392/surfinBH.git
cd surfinBH
git submodule init
git submodule update
python setup.py install
```

If you do not have root permissions, replace the last step with
`python setup.py install --user`


## Dependencies
All of these can be installed through pip or conda.
* [numpy](https://docs.scipy.org/doc/numpy/user/install.html)
* [scipy](https://www.scipy.org/install.html)
* [h5py](http://docs.h5py.org/en/latest/build.html)
* [scikit-learn](http://scikit-learn.org/stable/install.html) (at least 0.19.1)
* [lalsuite](https://pypi.org/project/lalsuite) (at least 6.70)
* [gwsurrogate](https://pypi.org/project/gwsurrogate)


## Usage

```python
import surfinBH
```

### See list of available fits
```python
print(list(surfinBH.fits_collection.keys()))
>>> ['NRSur3dq8Remnant', 'surfinBH7dq2', 'NRSur7dq4Remnant', 'NRSur7dq4EmriRemnant', 'NRSur3dq8_RD', 'NRSur3dq8BMSRemnant']
```

Pick your favorite fit and get some basic information about it.
```python
fit_name = 'NRSur7dq4Remnant'

surfinBH.fits_collection[fit_name].desc
>>> 'Fits for remnant mass, spin and kick veclocity for generically precessing BBH systems up to mass ratio 4.'

surfinBH.fits_collection[fit_name].refs
>>> 'arxiv:1905.09300'
```

### Load the fit
This only needs to be done **once** at the start of your script.
If the fit data is not already downloaded, this will also download the data.
```python
fit = surfinBH.LoadFits(fit_name)
>>> Loaded NRSur7dq4Remnant fit.
```
### Evaluation
The evaluation of each fit is different, so be sure to read the documentation.
This also describes the frames in which different quantities are defined.
```python
help(fit)
```

We also provide ipython examples for usage of different fits:

##### Current fits

* [NRSur7dq4Remnant](https://github.com/vijayvarma392/surfinBH/blob/master/examples/example_7dq4.ipynb) (Ref. [2])

* [NRSur7dq4EmriRemnant](https://github.com/vijayvarma392/surfinBH/blob/master/examples/example_7dq4Emri.ipynb) (Ref. [3])

* [NRSur3dq8Remnant](https://github.com/vijayvarma392/surfinBH/blob/master/examples/example_3dq8.ipynb) (called surfinBH3dq8 in Ref. [1])

* [NRSur3dq8_RD](https://github.com/vijayvarma392/surfinBH/blob/master/examples/example_3dq8_RD.ipynb) (Ref. [4])

* [NRSur3dq8BMSRemnant](https://github.com/vijayvarma392/surfinBH/blob/master/examples/example_3dq8BMS.ipynb) (Ref. [5]) 

##### Deprecated fits

* [surfinBH7dq2](https://github.com/vijayvarma392/surfinBH/blob/master/examples/example_7dq2.ipynb) (Ref. [1]. Superseded by NRSur7dq4Remnant)

## Animations

We also provide a tool to visualize the binary black hole scattering process,
see
[binary black hole explorer](https://vijayvarma392.github.io/binaryBHexp/).
Here's an example:

<img src="https://raw.githubusercontent.com/vijayvarma392/binaryBHexp/master/animations/video.gif" width="500"/>


## Making contributions
See this
[README](https://github.com/vijayvarma392/surfinBH/blob/master/README_developers.md)
for instructions on how to make contributions to this package.



## Credits
The code is maintained by [Vijay Varma](https://vijayvarma.com).
You can find the list of contributors
[here](https://github.com/vijayvarma392/surfinBH/graphs/contributors).
Please report bugs by raising an
issue on our [GitHub](https://github.com/vijayvarma392/surfinBH) repository.
